awesome-slash

AI models can write code. That's not the hard part anymore. The hard part is everything else—picking what to work on, managing branches, reviewing output, cleaning up artifacts, handling CI, addressing comments, deploying. awesome-slash automates the entire workflow, not just the coding.

Building custom skills, agents, hooks, or MCP tools? agnix is the CLI + LSP linter that catches config errors before they fail silently - real-time IDE validation, auto suggestions, auto-fix, and 155 rules for Cursor, Claude Code, Cline, Copilot, Codex, Windsurf, and more.

What This Is

Production-ready skills, agents, and commands for Claude Code, OpenCode, and Codex CLI.

Install the plugins → get the skills → your agents become more capable. Each piece was built to work with the others. The whole system is E2E tested.

From messy project to clean codebase. From drifted plan to focused execution. From task to merged PR.

Works with: Claude Code · OpenCode · Codex CLI

The Approach

Code does code work. AI does AI work.

• Detection: regex, AST analysis, static analysis—fast, deterministic, no tokens wasted
• Judgment: LLM calls for synthesis, planning, review—where reasoning matters
• Result: 77% fewer tokens for /drift-detect vs multi-agent approaches, certainty-graded findings throughout

Certainty levels exist because not all findings are equal:

| Level | Meaning | Action | |-------|---------|--------| | HIGH | Definitely a problem | Safe to auto-fix | | MEDIUM | Probably a problem | Needs context | | LOW | Might be a problem | Needs human judgment |

This came from testing on 1,000+ repositories.

Commands

| Command | What it does | |---------|--------------| | /next-task | Task → exploration → plan → implementation → review → ship | | /agnix | Lint agent configs - 155 rules for Skills, Memory, Hooks, MCP across 10+ AI tools | | /ship | Branch → PR → CI → reviews addressed → merge → cleanup | | /deslop | 3-phase detection pipeline, certainty-graded findings | | /perf | 10-phase performance investigation with baselines and profiling | | /drift-detect | AST-based plan vs code analysis, finds what's documented but not built | | /audit-project | Multi-agent code review, iterates until issues resolved | | /enhance | Analyzes prompts, agents, plugins, docs, hooks, skills | | /repo-map | AST symbol and import mapping via ast-grep | | /sync-docs | Finds outdated references, stale examples, missing CHANGELOG entries | | /learn | Research any topic, gather online sources, create learning guide with RAG index | | /consult | Consult another AI CLI tool for a second opinion. Use when you want to cross-check ideas, get alternative approaches, or validate decisions with Gemini, Codex, Claude, OpenCode, or Copilot. |

Each command works standalone. Together, they form complete workflows.

Skills

27 skills included across the plugins:

| Category | Skills | |----------|--------| | Performance | perf:perf-analyzer, perf:perf-baseline-manager, perf:perf-benchmarker, perf:perf-code-paths, perf:perf-investigation-logger, perf:perf-profiler, perf:perf-theory-gatherer, perf:perf-theory-tester | | Enhancement | enhance:enhance-agent-prompts, enhance:enhance-claude-memory, enhance:enhance-cross-file, enhance:enhance-docs, enhance:enhance-hooks, enhance:enhance-orchestrator, enhance:enhance-plugins, enhance:enhance-prompts, enhance:enhance-skills | | Workflow | next-task:discover-tasks, next-task:orchestrate-review, next-task:validate-delivery | | Cleanup | deslop:deslop, sync-docs:sync-docs | | Analysis | drift-detect:drift-analysis, repo-map:repo-mapping | | Productivity | consult:consult | | Learning | learn:learn | | Linting | agnix:agnix |

Skills give your agents specialized capabilities. When you install a plugin, its skills become available to all agents in that session.

Quick Navigation

| Section | What's there | |---------|--------------| | The Approach | Why it's built this way | | Commands | All 12 commands overview | | Skills | 27 skills across plugins | | Command Details | Deep dive into each command | | How Commands Work Together | Standalone vs integrated | | Design Philosophy | The thinking behind the architecture | | Installation | Get started | | Research & Testing | What went into building this | | Documentation | Links to detailed docs |

Command Details

/next-task

Purpose: Complete task-to-production automation.

What happens when you run it:

1. Policy Selection - Choose task source (GitHub issues, GitLab, local file), priority filter, stopping point
2. Task Discovery - Shows top 5 prioritized tasks, you pick one
3. Worktree Setup - Creates isolated branch and working directory
4. Exploration - Deep codebase analysis to understand context
5. Planning - Designs implementation approach
6. User Approval - You review and approve the plan (last human interaction)
7. Implementation - Executes the plan
8. Pre-Review - Runs deslop-agent and test-coverage-checker
9. Review Loop - Multi-agent review iterates until clean
10. Delivery Validation - Verifies tests pass, build passes, requirements met
11. Docs Update - Updates CHANGELOG and related documentation
12. Ship - Creates PR, monitors CI, addresses comments, merges

Phase 9 uses the orchestrate-review skill to spawn parallel reviewers (code quality, security, performance, test coverage) plus conditional specialists.

Agents involved:

| Agent | Model | Role | |-------|-------|------| | task-discoverer | sonnet | Finds and ranks tasks from your source | | worktree-manager | haiku | Creates git worktrees and branches | | exploration-agent | opus | Deep codebase analysis before planning | | planning-agent | opus | Designs step-by-step implementation plan | | implementation-agent | opus | Writes the actual code | | test-coverage-checker | sonnet | Validates tests exist and are meaningful | | delivery-validator | sonnet | Final checks before shipping | | ci-monitor | haiku | Watches CI status | | ci-fixer | sonnet | Fixes CI failures and review comments | | simple-fixer | haiku | Executes mechanical edits |

Cross-plugin agent: | Agent | Plugin | Role | |-------|--------|------| | deslop-agent | deslop | Removes AI artifacts before review | | sync-docs-agent | sync-docs | Updates documentation |

Usage:

/next-task              # Start new workflow
/next-task --resume     # Resume interrupted workflow
/next-task --status     # Check current state
/next-task --abort      # Cancel and cleanup

Full workflow documentation →

/agnix

Purpose: Lint agent configurations before they break your workflow. The first dedicated linter for AI agent configs.

agnix is a standalone open-source project that provides the validation engine. This plugin integrates it into your workflow.

The problem it solves:

Agent configurations are code. They affect behavior, security, and reliability. But unlike application code, they have no linting. You find out your SKILL.md is malformed when the agent fails. You discover your hooks have security issues when they're exploited. You realize your CLAUDE.md has conflicting rules when the AI behaves unexpectedly.

agnix catches these issues before they cause problems.

What it validates:

| Category | What It Checks | |----------|----------------| | Structure | Required fields, valid YAML/JSON, proper frontmatter | | Security | Prompt injection vectors, overpermissive tools, exposed secrets | | Consistency | Conflicting rules, duplicate definitions, broken references | | Best Practices | Tool restrictions, model selection